AASERT93- Weather Analysis and Prediction Using Empirical Orthogonal Functions.

Abstract

The primary purpose of AASERT Grant F49620-93-1-0531 was to support graduate student Scott Applequist's efforts to explore statistical methods of weather prediction under the supervision of Professor Pfeffer. The research Scott has done under this grant has enabled him to formulate his Ph. D. dissertation on cold season regional weather prediction in the range of 6 to 36 hours. His dissertation will be completed under AFOSR Grant F49620- 96-1-0172. Owing to the availability of plentiful surface and upper air data in both space and time over the eastern portion of the United States, Scott has chosen to test various nonlinear statistical methodologies over this region. Once successful methodologies are found, they can be tested over areas with more sparse data coverage. Scott's goal is to ascertain the extent to which nonlinear statistical methods can improve upon linear regression techniques and upon the accuracy of current weather forecasts.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1996
Accession Number
ADA315315

Entities

People

  • Richard L. Pfeffer

Organizations

  • Florida State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Advection
  • Air Force
  • Algorithms
  • Computational Science
  • Correlation Analysis
  • Data Science
  • Data Sets
  • Equations
  • Errors
  • Fluid Dynamics
  • Information Science
  • Neural Networks
  • United States
  • Water Vapor
  • Weather
  • Weather Forecasting

Readers

  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation
  • Research Science/Academic Research

Technology Areas

  • Space